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基于质心的样本加权聚类算法
引用本文:韦相,李志勇,朱永缤.基于质心的样本加权聚类算法[J].成都大学学报(自然科学版),2011,30(2):168-170.
作者姓名:韦相  李志勇  朱永缤
作者单位:红河学院计算机科学与技术系,云南蒙自,661100
基金项目:云南省教育厅科研基金(7C40843)资助项目
摘    要:针对传统的以k-means为代表的分割聚类算法认为所有的聚类样本对聚类中心的影响都是相同的这一观点,提出基于样本加权的聚类算法,并采用实际数据集验证算法的有效性.实验表明,该算法比传统的k-means聚类算法具有更高的精确度.

关 键 词:k-means算法  聚类  样本加权  质心

Algorithm of Sample's Weighting Clustering Based on Centroid
WEI Xiang,LI Zhiyong,ZHU Yongbin.Algorithm of Sample's Weighting Clustering Based on Centroid[J].Journal of Chengdu University (Natural Science),2011,30(2):168-170.
Authors:WEI Xiang  LI Zhiyong  ZHU Yongbin
Institution:WEI Xiang,LI Zhiyong,ZHU Yongbin(Department of Computer Science and Technology,Honghe University,Mengzi 661100,China)
Abstract:The traditional partitional clustering algorithm represented by k-means considers all the clustering samples have the same impacts on clustering center.In view of this point,a clustering algorithm was proposed to deal with different samples' weight and was applied to the evaluation of teaching quality.To evaluate the proposed algorithm,some real and artificial dataset were used to verify the effectiveness of the algorithm.The findings show that the proposed algorithm has higher precision than the traditiona...
Keywords:k-means algorithm  clustering  sample's weighting  centroid  
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